What is Local Advertising and How Does it Work? [+ Examples]

A couple of years ago, I ran to every grocery store and convenience store in my area, looking for one specific thing.
I wasn’t going to rest until I found it, and it took months upon months of searching high and low, almost every week, until finally, my eyes settled on the slender, enticing beauty in front of me, right there in my local grocery store.
A bottle of Coke with my name on it.

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AI And Data: A Pain Or Gain? Here’s What The Future Looks Like

Yes, it’s AI again! Artificial Intelligence (AI) is always in the limelight from the last couple of years. Mostly it is considered as a blessing to the IT world. However, many experts have shown their doubtfulness too. No, you just can’t say “Ok Boomer” here! Of course, they have greater reasons i.e. a threat to data security.

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Orbital resonance in Neptune’s moons

Phys.com published an article a couple days ago NASA finds Neptune moons locked in ‘dance of avoidance’. The article is based on the scholarly paper Orbits and resonances of the regular moons of Neptune.
The two moons closest to Neptune, named Naiad and Thalassa, orbit at nearly the same distance, 48,224 km for Naiad and 50,074 km for Thalassa.

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How to Improve Your Subscription-Based Business by Predicting Churn

A couple of weeks ago I wrote a guest post on churn prediction for Kissmetrics, and they just published it.
Churn prediction is one of the most popular Big Data use cases in business. It consists in detecting which customers are likely to cancel a subscription to a service based on how they use the service.

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To do: Construct a build-your-own-relevant-statistics-class kit.

Alexis Lerner, who took a couple of our courses on applied regression and communicating data and statistics, designed a new course, “Jews: By the Numbers,” at the University of Toronto:
But what does it mean to work with data and statistics in a Jewish studies course?

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Key learnings from Strata Barcelona 2014

Immediately after PAPIs.io ’14 — write-up coming soon! — I spent a couple of days at Strata in Barcelona.
Strata has several tracks and I ended up going mostly to “business” sessions, but this synthesis of things I heard at the conference will be of interest to technical people as well.

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Winning the Netflix Prize: A Summary

How was the Netflix Prize won? I went through a lot of the Netflix Prize papers a couple years ago, so I’ll try to give an overview of the techniques that went into the winning solution here.
Normalization of Global Effects
Suppose Alice rates Inception 4 stars. We can think of this rating as composed of several parts:
A baseline rating (e.g.

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Fab failure

So, I was browsing exp.lore.com and came across these nifty little usb-sticks a couple of days ago. Huh, that’s a pretty decent just-in-time gift I thought – might be an idea to buy a couple of them for those occasions where you don’t really have time to buy a gift for someone. So I click the link, and end up on the fine site fab.com.

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Edge Prediction in a Social Graph: My Solution to Facebook’s User Recommendation Contest on Kaggle

A couple weeks ago, Facebook launched a link prediction contest on Kaggle, with the goal of recommending missing edges in a social graph. I love investigating social networks, so I dug around a little, and since I did well enough to score one of the coveted prizes, I’ll share my approach here.

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Box-Plots for Education Recap

I stumbled across a brand new ML competition platform a couple of months ago, DrivenData, which describes itself as hosting “data science competitions to save the world”. Basically think Kaggle for non-profits. They had launched their first prize awarding comp, Box-Plots for Education which aimed to automatically classify education expenses into various categories.

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On Being Model-driven: Metrics and Monitoring

This article covers a couple of key Machine Learning (ML) vital signs to consider when tracking ML models in production to ensure model reliability, consistency and performance in the future. Many thanks to Don Miner for collaborating with Domino on this article. For additional vital signs and insight beyond what is provided in this article, attend the webinar.

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Design Decisions for the First Embedded Analytics Open-Source Framework

Design Decisions for the First Embedded Analytics Open-Source Framework For the last couple of years, we’ve been working on Cube.js, an analytics framework built specifically for customization and embedding. There are a lot of great tools data engineers can use to build internal data infrastructure.

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The data deluge means no reasonable expectation of privacy – now what?

Today a couple of different things reminded me about something that I suppose many people are talking about but has been on my mind as well.
The idea is that many of our societies social norms are based on the reasonable expectation of privacy. But the reasonable expectation of privacy is increasingly a thing of the past.

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